Fig 3

Main Panels

Fig 3A - Cell type proyection (UMAP)

Fig 3B - Protein markers in UMAP proyection

## TableGrob (2 x 7) "arrange": 13 grobs
##     z     cells    name           grob
## 1   1 (1-1,1-1) arrange gtable[layout]
## 2   2 (1-1,2-2) arrange gtable[layout]
## 3   3 (1-1,3-3) arrange gtable[layout]
## 4   4 (1-1,4-4) arrange gtable[layout]
## 5   5 (1-1,5-5) arrange gtable[layout]
## 6   6 (1-1,6-6) arrange gtable[layout]
## 7   7 (1-1,7-7) arrange gtable[layout]
## 8   8 (2-2,1-1) arrange gtable[layout]
## 9   9 (2-2,2-2) arrange gtable[layout]
## 10 10 (2-2,3-3) arrange gtable[layout]
## 11 11 (2-2,4-4) arrange gtable[layout]
## 12 12 (2-2,5-5) arrange gtable[layout]
## 13 13 (2-2,6-6) arrange gtable[layout]

Fig 3C - Barplot cell types + dendrogram

Fig 3D - Correlation plot Immune cells vs Endothelial cells

## `geom_smooth()` using formula 'y ~ x'

## `geom_smooth()` using formula 'y ~ x'

Supplementary info

S. Figure on cell type abundances G vs P

## 
## Attaching package: 'operators'
## The following objects are masked from 'package:base':
## 
##     options, strrep
## Warning: package 'dplyr' was built under R version 3.6.2
## 
## Attaching package: 'dplyr'
## The following object is masked from 'package:operators':
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##     %>%
## The following object is masked from 'package:gridExtra':
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##     combine
## The following objects are masked from 'package:stats':
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##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
##      cell_type   p.value FDR_corrected
## 1   Epithelial 0.9142857     0.9142857
## 2  Endothelial 0.1714286     0.6000000
## 3  Mesenchymal 0.4761905     0.6666667
## 4 Other_immune 0.7619048     0.8888889
## 5      Myeloid 0.3523810     0.6166667
## 6     Tc_cells 0.1714286     0.6000000
## 7     Th_cells 0.3523810     0.6166667
## Using pt_ID, CANARY as id variables

S. Figure on protein expression by cell type G vs P

## Warning in wilcox.test.default(exp_median[ig1, i], exp_median[ig2, i]): cannot
## compute exact p-value with ties

## Warning in wilcox.test.default(exp_median[ig1, i], exp_median[ig2, i]): cannot
## compute exact p-value with ties

## Warning in wilcox.test.default(exp_median[ig1, i], exp_median[ig2, i]): cannot
## compute exact p-value with ties

## Warning in wilcox.test.default(exp_median[ig1, i], exp_median[ig2, i]): cannot
## compute exact p-value with ties

## Warning in wilcox.test.default(exp_median[ig1, i], exp_median[ig2, i]): cannot
## compute exact p-value with ties

## Warning in wilcox.test.default(exp_median[ig1, i], exp_median[ig2, i]): cannot
## compute exact p-value with ties

## Warning in wilcox.test.default(exp_median[ig1, i], exp_median[ig2, i]): cannot
## compute exact p-value with ties

## Warning in wilcox.test.default(exp_median[ig1, i], exp_median[ig2, i]): cannot
## compute exact p-value with ties

## Warning in wilcox.test.default(exp_median[ig1, i], exp_median[ig2, i]): cannot
## compute exact p-value with ties

## Warning in wilcox.test.default(exp_median[ig1, i], exp_median[ig2, i]): cannot
## compute exact p-value with ties

## Warning in wilcox.test.default(exp_median[ig1, i], exp_median[ig2, i]): cannot
## compute exact p-value with ties

## Warning in wilcox.test.default(exp_median[ig1, i], exp_median[ig2, i]): cannot
## compute exact p-value with ties

## Warning in wilcox.test.default(exp_median[ig1, i], exp_median[ig2, i]): cannot
## compute exact p-value with ties

Endothelial cells

## Using CANARY, pt_ID as id variables

##              Protein   p.value FDR_corrected
## 1      144Nd_HLA-ABC 0.1714286     0.7619048
## 2         145Nd_CD31 0.4761905     0.7619048
## 3  146Nd_Thioredoxin 0.3523810     0.7619048
## 4        147Sm_b-CAT 0.4761905     0.7619048
## 5     156Gd_Vimentin 1.0000000     1.0000000
## 6      158Gd_p-STAT3 0.7619048     0.8465608
## 7         160Gd_MDM2 0.6095238     0.7619048
## 8  161Dy_Cytokeratin 0.4761905     0.7619048
## 9         163Dy_TP63 0.6095238     0.7619048
## 10      174Yb_HLA-DR 0.1714286     0.7619048

Fibroblasts/Mesenchymal cells

## Using CANARY, pt_ID as id variables
## Warning in wilcox.test.default(c(0, 0.0958118253303701, 0.284162729407862, :
## cannot compute exact p-value with ties
## Warning in wilcox.test.default(c(0.802649816095183, 0.215492384630114,
## 0.0605647943338007, : cannot compute exact p-value with ties

##          Protein    p.value FDR_corrected
## 1    141Pr_EpCAM 0.76190476     0.9142857
## 2   142Nd_ccasp3 0.91428571     0.9142857
## 3     155Gd_CD56 0.47619048     0.8571429
## 4 156Gd_Vimentin 0.91428571     0.9142857
## 5  158Gd_p-STAT3 0.11428571     0.5142857
## 6     160Gd_MDM2 0.19945761     0.5983728
## 7     163Dy_TP63 0.47619048     0.8571429
## 8      170Yb_CD3 0.91406196     0.9142857
## 9   174Yb_HLA-DR 0.03809524     0.3428571

Immune cells

## Using CANARY, pt_ID as id variables
## Warning in wilcox.test.default(c(3.06708656196431, 0.066910551904235,
## 3.04431780411568, : cannot compute exact p-value with ties
## Warning in wilcox.test.default(c(0.202586121632867, 0.0645635010399363, : cannot
## compute exact p-value with ties
## Warning in wilcox.test.default(c(0.501727573634015, 0.130067040154415,
## 0.712432219756351, : cannot compute exact p-value with ties

##           Protein   p.value FDR_corrected
## 1   144Nd_HLA-ABC 0.1055017     0.8571429
## 2      154Sm_CD45 0.4761905     0.9523810
## 3  156Gd_Vimentin 0.4761905     0.9523810
## 4   158Gd_p-STAT3 0.7619048     0.9523810
## 5       159Tb_CD4 0.9140620     1.0000000
## 6      163Dy_TP63 0.6095238     0.9523810
## 7      166Er_CD44 1.0000000     1.0000000
## 8       170Yb_CD3 0.7619048     0.9523810
## 9     171Yb_CD11b 0.3314247     0.9523810
## 10   174Yb_HLA-DR 0.1714286     0.8571429

CD8 T cells

## Using CANARY, pt_ID as id variables

##          Protein    p.value FDR_corrected
## 1  144Nd_HLA-ABC 0.03174603     0.2539683
## 2     154Sm_CD45 0.90476190     0.9047619
## 3 156Gd_Vimentin 0.55555556     0.8344671
## 4     163Dy_TP63 0.19047619     0.5079365
## 5     166Er_CD44 0.73015873     0.8344671
## 6      168Er_CD8 0.55555556     0.8344671
## 7      170Yb_CD3 0.73015873     0.8344671
## 8   174Yb_HLA-DR 0.11111111     0.4444444

CD4 T cells

## Using CANARY, pt_ID as id variables
## Warning in wilcox.test.default(c(0, 0.0561621657336121, 0, 0), c(0, 0,
## 1.50456532271426, : cannot compute exact p-value with ties

##          Protein   p.value FDR_corrected
## 1  144Nd_HLA-ABC 0.6095238     0.9142857
## 2     154Sm_CD45 0.3523810     0.7928571
## 3 156Gd_Vimentin 0.2571429     0.7714286
## 4      159Tb_CD4 0.6095238     0.9142857
## 5     163Dy_TP63 0.7619048     0.9795918
## 6     166Er_CD44 0.1714286     0.7714286
## 7     169Tm_CD24 1.0000000     1.0000000
## 8      170Yb_CD3 0.2571429     0.7714286
## 9   174Yb_HLA-DR 0.9142857     1.0000000

Myeloid cells

## Using CANARY, pt_ID as id variables
## Warning in wilcox.test.default(c(3.30075534359615, 0.0972935332589382,
## 3.31354462816258, : cannot compute exact p-value with ties
## Warning in wilcox.test.default(c(1.62386202915046, 0.717296683223608,
## 2.44717234480325, : cannot compute exact p-value with ties
## Warning in wilcox.test.default(c(0.748820669157824, 0.123253874437529,
## 1.67192224879611, : cannot compute exact p-value with ties
## Warning in wilcox.test.default(c(0.63662474810693, 0.0913139040611759,
## 1.20841095112529, : cannot compute exact p-value with ties

##              Protein   p.value FDR_corrected
## 1      144Nd_HLA-ABC 0.1645218     0.9523810
## 2         145Nd_CD31 0.4541743     0.9523810
## 3  146Nd_Thioredoxin 0.5929097     0.9846154
## 4         154Sm_CD45 0.4761905     0.9523810
## 5     156Gd_Vimentin 0.4761905     0.9523810
## 6      158Gd_p-STAT3 0.3523810     0.9523810
## 7          159Tb_CD4 0.7461278     0.9846154
## 8         160Gd_MDM2 0.9142857     0.9846154
## 9         163Dy_TP63 1.0000000     1.0000000
## 10        166Er_CD44 0.9142857     0.9846154
## 11       171Yb_CD11b 0.4761905     0.9523810
## 12        172Yb_p-S6 0.9142857     0.9846154
## 13      174Yb_HLA-DR 0.2571429     0.9523810
## 14       175Lu_PD-L1 0.7619048     0.9846154

Epithelial cells

## Using CANARY, pt_ID as id variables
## Warning in wilcox.test.default(c(2.33079293987923, 0.0582644008491126,
## 1.75087785796523, : cannot compute exact p-value with ties
## Warning in wilcox.test.default(c(1.63156525887895, 0.322305842850225,
## 1.32203451663395, : cannot compute exact p-value with ties
## Warning in wilcox.test.default(c(1.13653172069154, 0.0527562183492093,
## 1.50292979733778, : cannot compute exact p-value with ties

##              Protein    p.value FDR_corrected
## 1        141Pr_EpCAM 0.11428571     0.4114286
## 2       142Nd_ccasp3 0.35238095     0.5714286
## 3      144Nd_HLA-ABC 0.16452182     0.4408163
## 4        147Sm_b-CAT 0.17142857     0.4408163
## 5         148Nd_HER2 0.03809524     0.4114286
## 6         151Eu_TTF1 0.09898793     0.4114286
## 7         154Sm_CD45 0.47619048     0.5714286
## 8         155Gd_CD56 0.76190476     0.8067227
## 9     156Gd_Vimentin 0.47619048     0.5714286
## 10     158Gd_p-STAT3 0.35238095     0.5714286
## 11        160Gd_MDM2 0.91428571     0.9142857
## 12 161Dy_Cytokeratin 0.11428571     0.4114286
## 13         162Dy_MET 0.25714286     0.5142857
## 14        163Dy_TP63 0.47619048     0.5714286
## 15         164Dy_CK7 0.47619048     0.5714286
## 16        165Ho_EGFR 0.10550173     0.4114286
## 17         170Yb_CD3 0.60952381     0.6857143
## 18      174Yb_HLA-DR 0.25714286     0.5142857

Fig 4

Main Panels

Fig 4A - Epithelial clusters proyection (UMAP)

## Warning: Removed 28 rows containing non-finite values (stat_density2d).
## Warning: Removed 28 rows containing missing values (geom_point).

## Warning: Removed 28 rows containing missing values (geom_point).

## Warning: Removed 28 rows containing missing values (geom_point).

## Warning: Removed 28 rows containing missing values (geom_point).

Fig 4B - Barplot cell types + dendrogram

Fig 4C - Protein markers by cluster heatmap

## 
## Attaching package: 'gplots'
## The following object is masked from 'package:stats':
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##     lowess

Fig 4D - Correlation plot Immune cells vs Endothelial cells

## Warning: Ignoring unknown parameters: label.size
## `geom_smooth()` using formula 'y ~ x'

## Warning: Ignoring unknown parameters: label.size
## `geom_smooth()` using formula 'y ~ x'

Supplementary info

S. Figure on cluster abundances G vs P

##        cell_type   p.value FDR_corrected
## 1   Epithelial_1 0.7619048     0.9142857
## 2   Epithelial_2 0.9142857     0.9142857
## 3   Epithelial_3 0.1714286     0.8571429
## 4   Epithelial_4 0.7619048     0.9142857
## 5   Epithelial_5 0.9142857     0.9142857
## 6   Epithelial_6 0.9142857     0.9142857
## 7   Epithelial_7 0.1714286     0.8571429
## 8   Epithelial_8 0.3523810     0.8809524
## 9   Epithelial_9 0.3523810     0.8809524
## 10 Epithelial_10 0.6095238     0.9142857
## Using pt_ID, CANARY as id variables